Led by Erica Weiss, PhD, and Jessica Zwerling, MD, Montefiore Einstein is conducting an observational study to develop and identify vocal biomarkers for the screening and monitoring of cognitive decline in older adults and to help detect and predict the onset of cognitive impairment associated with disorders such as Alzheimer’s disease and other dementias. Our clinician-scientists at Montefiore Einstein Center for the Aging Brain and Montefiore Einstein Memory Disorders Center are examining the potential use of a new, non-invasive digital voice analysis technology which incorporates audio signal processing and machine learning to identify subtle voice changes that may aid in the detection of mild cognitive impairment. This vocal biomarker system, which uses a smartphone-based app and digital audio recording, analyzes the acoustic features of voice changes using artificial intelligence. 

Acoustic and linguistic changes in day to day speech have been identified in individuals experiencing cognitive decline. In this study, the aim is to identify vocal biomarkers that are correlated with specific cognitive diagnoses based on a neuropsychologist-derived algorithm of each participant’s clinical performance on cognitive measures. 

Developing a vocal biomarker-based risk assessment could enable frequent and real-time speech analysis using an individual’s own digital device within their own home. The hope is that this vocal biomarker platform can help with the screening, early detection and monitoring of individuals suffering from or at risk of cognitive decline, including early-stage Alzheimer’s disease and other forms of dementia. The platform could potentially also help to  assess response to treatment and to provide remote healthcare.